Tag Archives: Edge

The 2018 Vancouver OpenStack Summit is very focused on IT infrastructure at the Edge. It’s a fitting topic considering the telcos’ embrace for the project; however, building the highly distributed, small footprint management needed for these environments is very different than OpenStack’s architectural priorities. There is a significant risk that the community’s bias towards it’s current code base (which still has work needed to service hyper-scale and enterprise data centers) will undermine progress in building suitable Edge IT solutions.

There are five significant ways that Edge is different than “traditional” datacenter. We often discuss this on our L8istSh9y podcast and it’s time to summarize them in a blog post.

IT infrastructure at the Edge is different than “edge” in general. Edge is often used as a superset of Internet of Things (IoT), personal devices (phones) and other emerging smart devices. Our interest here is not the devices but the services that are the next hop back supporting data storage, processing, aggregation and sharing. To scale, these services need to move from homes to controlled environments in shared locations like 5G towers, POP and regional data centers.

Unlike built-to-purpose edge devices, the edge infrastructure will be built on generic commodity hardware.

Here are five key ways that managing IT infrastructure at the edge is distinct from anything we’ve built so far:

Highly Distributed – Even at hyper-scale, we’re used to building cloud platforms in terms of tens of data centers; however, edge infrastructure sites will number in the thousands and millions! That’s distinct management sites, not servers or cores. Since the sites will not have homogeneous hardware specifications, the management of these sites requires zero-touch management that is vendor neutral, resilient and secure.

Low Latency Applications – Latency is the reason why Edge needs to be highly distributed. Edge applications like A/R, V/R, autonomous robotics and even voice controls interact with humans (and other apps) in ways that require microsecond response times. This speed of light limitation means that we cannot rely on hyper-scale data centers to consolidate infrastructure; instead, we have to push that infrastructure into the latency range of the users and devices.

Decentralized Data – A lot of data comes from all of these interactive edge devices. In our multi-vendor innovative market, data from each location could end up being sprayed all over the planet. Shared edge infrastructure provides an opportunity to aggregate this data locally where it can be shared and (maybe?) controlled. This is a very hard technical and business problem to solve. While it’s easy to inject blockchain as a possible solution, the actual requirements are still evolving.

Remote, In-Environment Infrastructure – To make matters even harder, the sites are not traditional raised floor data centers with 24×7 attendants: most will be small, remote and unstaffed sites that require a truck roll for services. Imagine an IT shed at the base of a vacant lot cell tower behind rusted chain link fences guarded by angry squirrels and monitored by underfunded FCC regulators.

Multi-Tenant and Trusted – Edge infrastructure will be a multi-tenant environment because it’s simple economics driving as-a-Service style resource sharing. Unlike buy-on-credit-card public clouds, the participants in the edge will have deeper, trusted relationships with the service providers. A high degree of trust is required because distributed application and data management must be coordinated between the Edge infrastructure manager and the application authors. This level of integration requires a deeper trust and inspect than current public clouds require.

These are hard problems! Solving them requires new thinking and tools that while cloud native in design, are not cloud tools. We should not expect to lift-and-shift cloud patterns directly into edge because the requirements are fundamentally different. This next wave of innovation requires building for an even more distributed and automated architecture.

I hope you’re as excited as we are about helping build infrastructure at the edge. What do you think the challenges are? We’d like to hear from you!

Dave works for Redis Labs organizing workshops, hackathons, meetups and other events to help developers learn when and how to use Redis. Dave is also the co-founder and lead organizer of CloudCamp, a community of Cloud Computing enthusiasts in over 100 cities around the world. Dave graduated from Cal Poly: San Luis Obispo and has worked in developer relations for 12 years at companies like PayPal, Strikeiron and Platform D. Dave gained modest notoriety when he proposed to his girlfriend in the book “PayPal Hacks.”

A common side-effect of rapid growth for any organization is the introduction of complexity and one-off solutions to keep things moving regardless of the long-term impact. Over time, these decisions add up to create a chaotic environment for IT teams who find themselves unable to find an appropriate time to stop and reset.

IT operations teams also struggle in this environment as management knowledge for all these technologies are not often shared appropriately and it is common to have only 1 operator capable of supporting specific technologies. Obviously, enterprises are at great risk when knowledge is not shared and there is no standard process across a team.

Issue : Infrastructure Management

One-Off Operations – Customized operation tooling per service leads to team dysfunction as operators cannot support each due to inexperience with unique tools

IT Productivity – Data centers struggle to meet business needs with no standard process or tools; cloud platforms expose this deficiency causing business to go shadow IT

Impact : Delivery Times

Costly and Slow – Many data centers operate with dated processes and tools causing significant delays in new service rollout as well as maintaining existing services

Cross Platform Support – IT teams MUST maintain control over company services by supporting internal data centers as well as cloud deployments from a single platform

I love great conversations about technology – especially ones where the answer is not very neatly settled into winners and losers (which is ALL of them in IT). I’m excited that RackN has (re)launched the L8ist Sh9y (aka Latest Shiny) podcast around this exact theme.

Please check out the deep and thoughtful discussion I just had with Mark Thiele (notes) of Aperca where we covered Mark’s thought on why public cloud will be under 20% of IT and culture issues head on.

While the RackN team and I have been heads down radically simplifying physical data center automation, I’ve still been tracking some key cloud infrastructure areas. One of the more interesting ones to me is Edge Infrastructure.

This once obscure topic has come front and center based on coming computing stress from home video, retail machine and distributed IoT. It’s clear that these are not solved from centralized data centers.

While I’m posting primarily on the RackN.com blog, I like to take time to bring critical items back to my personal blog as a collection. WARNIING: Some of these statements run counter to other industry. Please let me know what you think!

By far the largest issue of the Edge discussion was actually agreeing about what “edge” meant. It seemed as if every session had a 50% mandatory overhead in definitioning. Putting my usual operations spin on the problem, I choose to define edge infrastructure in data center management terms. Edge infrastructure has very distinct challenges compared to hyperscale data centers. Read article for the list...

Running each site as a mini-cloud is clearly not the right answer. There are multiple challenges here. First, any scale infrastructure problem must be solved at the physical layer first. Second, we must have tooling that brings repeatable, automation processes to that layer. It’s not sufficient to have deep control of a single site: we must be able to reliably distribute automation over thousands of sites with limited operational support and bandwidth. These requirements are outside the scope of cloud focused tools.

If “cloudification” is not the solution then where should we look for management patterns? We believe that software development CI/CD and immutable infrastructure patterns are well suited to edge infrastructure use cases. We discussed this at a session at the OpenStack OpenDev Edge summit.

What do YOU think? This is an evolving topic and it’s time to engage in a healthy discussion.